---
code_id: 175974
site_ownership_code: "LBNL"
open_source: true
repository_link: "https://github.com/liuyangzhuan/STFNO"
project_type: "OS"
software_type: "S"
official_use_only: {}
developers:
- email: "rahman@lbl.gov"
  orcid: ""
  first_name: "Mustafa"
  last_name: "Rahman"
  middle_name: ""
  affiliations:
  - "Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)"
- email: "liuyangzhuan@lbl.gov"
  orcid: ""
  first_name: "Yang"
  last_name: "Liu"
  middle_name: ""
  affiliations:
  - "Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)"
contributors: []
sponsoring_organizations:
- organization_name: "USDOE"
  funding_identifiers: []
  primary_award: "AC02-05CH11231"
  DOE: true
contributing_organizations: []
research_organizations:
- organization_name: "Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United\
    \ States)"
  DOE: true
related_identifiers: []
award_dois: []
release_date: "2025-02-04"
software_title: "Sparsified Time-dependent PDEs FNO (STFNO) v1.0.0"
acronym: "STFNO v1.0.0"
doi: "https://doi.org/10.11578/dc.20260219.2"
description: "STFNO (Sparsified Time-dependent PDEs FNO code) is an extension of the\
  \ popular Fourier Neural Operator (FNO) architecture to the solution of coupled\
  \ systems of time-dependent partial differential equations. STFNO leverages the\
  \ sparsified dependencies on the field quantities based on the semi-discretiezed\
  \ form of the PDEs, enabling significant reduction in the number of model parameters.\
  \ STFNO has been extensively tested on two fusion simulation codes, NIMROD and GTC,\
  \ and can be easily tailored to other systems of PDEs."
programming_languages: []
country_of_origin: "United States"
project_keywords: []
licenses:
- "BSD 3-clause \"New\" or \"Revised\" License"
recipient_org: "LBNL"
site_accession_number: "2025-025"
date_record_added: "2026-02-19"
date_record_updated: "2026-02-19"
is_file_certified: false
last_editor: "agithire@lbl.gov"
is_limited: false
links:
- rel: "citation"
  href: "https://www.osti.gov/doecode/biblio/175974"